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Multidisciplinary Design, Analysis and Optimization of Performance Adaptive Aeroelastic Wings

机译:性能自适应气动弹性翼的多学科设计,分析和优化

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A multidisciplinary design, analysis and optimization (MDAO) tool for designing composite aircraft with performance adaptive aeroelastic wings is presented in this paper. The MDAO framework is applied for designing a low-speed flying-wing composite aircraft as a testbed to demonstrate the active flutter suppression for flexible large aspect ratio wings. The Sparibs concept is considered for the wing box design by designing both spar and rib locations with manufacturing constraints in their shape for testbed. Both the structural weight and total drag reductions are considered as the objective functions for the flying-wing aircraft design subjected to various constraints including strength, buckling, stall lift limit, hinge moment and flutter. The worst load case of 3.8G maneuver load factor is used to determine the optimal internal structural layout and the optimal laminate configurations for the wing box resulting in minimal total weight. A hybrid optimization approach is used for the full structural optimization. An evolutionary algorithm is used to determine the optimal laminate configurations for wing skin laminates and sandwich panels, and spar and rib locations. For each population of the evolutionary algorithm, a gradient-based optimization is conducted to determine the optimal flaps resulting in the minimal wing root bending moment as a surrogate for the structural weight. Once the optimal sized structure is obtained, a gradient-based optimization is conducted to minimize the total drag by scheduling its flap rotations during 1G cruise.
机译:本文提出了一种多学科设计,分析和优化(MDAO)工具,用于设计具有性能自适应气动弹性机翼的复合材料飞机。 MDAO框架用于设计低速飞翼复合飞机作为试验台,以演示对柔性大长宽比机翼的主动扑动抑制。通过设计翼梁和肋骨的位置,并限制制造形状来限制试验台的翼梁设计,从而在翼盒设计中考虑了Sparibs概念。结构重量和总减阻都被认为是受各种约束(包括强度,屈曲,失速升力极限,铰链力矩和颤动)的飞行机翼设计的目标函数。 3.8G机动负载系数的最坏情况用于确定机翼盒的最佳内部结构布局和最佳层压板配置,从而使总重量最小。混合优化方法用于完整的结构优化。进化算法用于确定机翼蒙皮层压板和夹心板以及翼梁和肋骨位置的最佳层压板配置。对于进化算法的每个种群,进行基于梯度的优化来确定最佳襟翼,以产生最小的机翼根部弯矩作为结构重量的替代。一旦获得最佳尺寸的结构,便会进行基于梯度的优化,以通过在1G巡航期间安排其襟翼旋转来最大程度地减小总阻力。

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